I was reading a whitepaper by Aaron Zornes today (“2007-2008 Scorecards for Data Governance in the Global 5000 Enterprise”) and came across an interesting quote:
“Although many organizations have improved end-to-end business processes through CRM implementations, the challenge of developing a unified customer or product view has not been fully addressed by the application suite vendors. For example, enterprise CRM solutions such as Siebel Systems supposedly were to integrate sales, marketing and service functions but in reality provided mostly automation of the sales force with arduous and fragile interfaces between sales, service and marketing. Concurrently, enterprise resource planning (ERP) was marketed as the integration among accounting, manufacturing and distribution. In practice, large enterprises are now turning to MDM as the service-oriented architecture means of unifying both CRM and ERP individually as well to integrate the front office (CRM) and the back office (ERP) together. “
In my experiences over the past twenty years or so, the enterprise software implementations I’ve been part of have treated data and process integration as a “necessary evil”. Almost like a difficult proof in a college math class, where the professor takes you up to a certain point, and then as the class ends, calls out that “the rest of the proof is left as an exercise for the class”.
I’ve seen projects where several systems were supposed to be integrated but never were, or where the front office and back office were integrated through “manual integration”, i.e. manual re-keying of key customer and product information between the two systems.
Little wonder, then, that ERP and CRM investments in many cases failed to deliver their expected return on investment. And now large enterprises are turning to Master Data Management (MDM). Given that successful MDM implementations requires five essential elements (data governance, a hub platform, integration, data quality and external enrichment capabilities), the temptation is there for people to de-scope important aspects of MDM.
Just as critical interfaces were de-scoped from earlier ERP and CRM projects, we’ve started to see people trying to do MDM without data quality, and even without adequate integration.
But let’s collectively resist these temptations. MDM and data governance are “hot” right now because they offer the promise of accurate, complete, timely and consistent information across the enterprise.
If we start to compromise on the essential elements of MDM, or fail to address MDM’s interconnected nature of people, processes, technology and information by focusing only on the technology, then in the not-too-distant future, MDM will not only go through Gartner’s “Trough of Disillusionment”, but it will be largely discredited. The industry will miss out on some huge future opportunities, and global enterprises will miss out on the ability to invest in their people, redesign their processes, implement new technology for MDM and service-oriented architecture, and weave in external information to supplement their internal data.
We all understand the pressure in the corporate world to deliver results in one quarter or less, but let’s make sure our short term approach doesn’t compromise the long term vision so much that the longer term return on investment becomes unachievable.
“Data governance is critical to these master data management efforts and ultimately is the tipping point as to whether the MDM program’s business outcome achieves its intended ROI and long-term sustainability.”
So resist the temptation to identify the need for Master Data Management, and then immediately run out and engage a systems integrator to help you evaluate, select and deploy some MDM technology. Remember to invest (either up front or in parallel with your MDM selection and deployment) in defining a workable data governance organization with accompanying business processes.
By paying attention to the integration between data governance (i.e. the people and processes) and the MDM techology (hub platform, integration, data quality and external enrichment), you’ll dramatically increase your chances for the successful delivery of expected functionality and ROI, on time and on budget.